Titlebook: Deep Learning and Physics; Akinori Tanaka,Akio Tomiya,Koji Hashimoto Book 2021 The Editor(s) (if applicable) and The Author(s), under excl

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Hla461

Inverse Problems in Physicsto solve an inverse problem? What is the meaning of the phrase “machine learning is good at solving inverse problems”? You will gain a comprehensive perspective and significance in applying machine learning to theoretical physics.

Dysarthria

綠州

積習已深

Spinglass and Neural Networks The Hopfield model, which explains the mechanism of memory in terms of physics, is a bridge between physics and neural networks. In this chapter, we explain the Hopfield model and investigate the relationship between machine learning and spin glass, which is still a rich subject in condensed matter physics.

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上腭

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Introduction to Machine LearningIn this chapter, we learn the general theory of machine learning. We shall take a look at examples of what learning is, what is the meaning of “machines learned,” and what relative entropy is. We will learn how to handle data in probability theory, and describe “generalization” and its importance in learning.